Tuesday, March 03, 2015

...is the title of an interesting TV programme that was on BBC 4 last night. It is quite amazing that they dared to show such a maths/stats/science-heavy program at prime time, albeit on a minor channel, so I will start by commending them for that (the inevitable grumbles follow later). The three numbers they featured were the 0.85C warming since 1880s, 95% confidence that anthropogenic influence had caused most of this, and the 1 trillion tonnes of carbon that would take us to about 2C warming. I think it was originally planned to be three 30 minute programmes, but they ran it all together as one long piece, which seemed to work well to me.

I think they told the stories in an engaging manner, there was also lots of interesting historical stuff about how our understanding of the climate system has developed, which was mostly very well done and would probably have been even more interesting had I not already known it! But of course I was hardly the target audience.

In fact one of the researchers making the program contacted me last year to talk about Bayesian vs frequentist approaches to detection and attribution, specifically the IPCC's statement attributing most of the warming of the last century to anthropogenic effects. Unfortunately I wasn't able to be very encouraging about the idea of explaining the differences between Bayesian vs frequentist approaches to the general public, after all most climate scientists struggle with this question as is demonstrated by the IPCC's misrepresentation of D&A results! I've written on this (really must update my web pages, that link won't last for ever...or will it?) but the argument has little traction even in the climate science community because most people are quite content to continue in their comfortably-erroneous way.

Anyway, the Bayesian thing didn't make it into the transmitted programme, which I was neither surprised nor disappointed about, as I really can't see how to present it in such a way that the general public would get anything out of it. And the traditional misrepresentation of the probability of observations more extreme than observed given the null, as the probability of the null given the observations, was heavily featured (that's basically where the 95% comes from). Sigh. But what I really want to grumble about most strongly was the garbled and nonsensical representation of Kalman filtering in the first section, which, contrary to the claims in the programme, is not a method to check observations against each other and has not been used for temperature data homogenisation. The Kalman filter is actually used for updating a model prediction with new observations, and this is how it was used for space navigation. That is, based on current estimates of velocity and position at time t1, the equations of motion are used to predict the new position and velocity at subsequent time t2, and then imperfect observations of the position at t2 are used to update the estimates of position and velocity, and so on ad infinitum.

Ok, pedants may observe that NCEP has pioneered the use of an ensemble Kalman filter for its 20th century reanalysis project, but this is somewhat tangential to climate change and their results, interesting as they are, have their own homogenisation problems and are are hardly central to the debate on global warming. Ironically, Doug McNeall (who was involved as a scientific consultant, I'm not blaming him for anything in particular though) tweeted a link to the wikipedia page on Kalman filtering, which is a much better resource for anyone interested in learning more about the topic. Anyway, I'm really baffled as to where this bit came from - maybe they just couldn't resist a link to “rocket science” :-) Or did someone think “filter” might be related to filtering out bad data? Well, it isn't.

The “pixel sticks” were very clever, but I don't really think a line graph is improved by drawing it on wobbly axes, expecially if a straight line trend is then drawn through the data! I wonder if Doug will feature that on his Better Figures blog :-) And as for the presenters spending most of their time walking away from the camera...I'm probably sounding like a grumpy old man so I'd better stop. As I said, I think it was pretty good overall, but if you want a mathematical/statistical program that really doesn't make any concessions to dumbing down, and that does cover climate change (and Bayesian statistics) on occasion, I strongly recommend “More or Less” on Radio 4.

Update: Oh, this is interesting. It's a blog post about the programme from the mathematician (Norman Fenton) who presented the 95% section. Turns out he is actually a Bayesian who clearly understands how that number is tarnished by prosecutor's fallacy, and he argues that the scientific debate would be improved by a greater use of Bayesian methods!

Friday, February 27, 2015

I’ve just had a very enjoyable visit to the UKMO Hadley Centre, courtesy of Richard Betts. My talk was similar to the one I recently gave in Japan, which had been a bit clunky and unrehearsed in parts, so in the intervening weeks I revised it a bit which I think/hope made it a bit more coherent. Some of it was old stuff about single model vs multi-model ensembles (including work done ages ago in collaboration with UKMO people, in fact), and some was on model evaluation via paleoclimate simulations. I’ll not put the slides up online yet as this includes some unpublished work that I’m just a minor author on and which is under revision as I type. The last, still relatively unpolished, part of the talk concerned the thorny topic of model independence. I think I’ve now finally reached the point at which I’ve got enough material to write a paper on this. I’ve not usually worked this way round, but it seems that forcing oneself to put down thoughts sufficient to support a presentation can be a helpful way to kickstart the writing process. I had fun giving the talk, and judging from the questions after, many of the impressively large audience stayed awake.

The sun shone, so the UKMO building was particularly shiny and spectacular. I really like the design – easily the best science lab I’ve visited in that respect, though the open-plan interior arrangement is another matter. I didn’t dare take a picture – would probably have been carried away in an orange jump-suit if I had – so you’ll have to make do with this much better one off the web (borrowed from here).

We rounded things off with a lovely pub lunch with Richard, @dougmcneall and one other who despite our encouragement is still shying away from social media :-)

The Virgin Cross-country train (direct from Leeds) is not the most comfortable way to travel ("airline" seats seems a bit of poetic license), but it did get the job done. The grim north is not so remote after all! Now we’ve got a month at home to do some work, before the next set of trips kicks off.

Saturday, February 21, 2015

This is Riley, and he's up for adoption. We are fostering him for Bentham Pet Rescue. Apparently it is much better for homeless cats to stay in people's homes than at a cattery. He's been at the rescue since October and it is hard to imagine why he hasn't found a home as he is as big and furry a cat as you could hope for. He also plays games, demands to be stroked by head butting, and purrs whenever you go near him. He talks quite a lot and comes when called, and hasn't even broken any of our belongings yet. Having only been in the house only 24 hours, he still seems a little lost, wondering what is going to happen next. We are at home for quite a bit of the day, so we are hoping he will adjust to being a bit less nocturnal.

Tuesday, February 17, 2015

I'm not sure if either of my readers is interested in spending a(nother!) season in a primitive hut with only penguins for company (slight exaggeration, reports indicate it's more Shinjuku station than Scott of the Antarctic), but if not you can always play “guess the relative” with the photos in the job advert instead :-)

Monday, February 16, 2015

Just had two weeks in Japan, mostly visiting our friends and colleagues in AORI and NIES. These institutes are both some way outside Tokyo but on the same train line out of Tokyo, so we stayed in Asakusa, close by the famous Senso-ji temple

and very convenient for seeing various other friends and enjoying all of Tokyo’s attractions.

Not ignoring Hinode, which strange as it may seem, is also well within Tokyo’s boundaries!

AORI always seems a bit of strange and desolate place, part of a large research campus of Tokyo University, which was basically built in the middle of nowhere a decade ago but around which shops and services are gradually expanding. It still seems very empty though.

The scientific content of the trip was mostly focussed around paleoclimate stuff, particularly how the strength and stability of the North Atlantic component of the overturning circulation might have changed in past glacial cycles. We were working on this previously with a postdoc who transferred to AORI (along with her funding) when we left. Hopefully there will be more to say on these topics in the future, as papers are written. The visit to NIES was more of an exchange of updates, I gave a seminar and then the group we had collaborated with all summarised their latest work. Rather like the old JUMP meetings we used to have, in fact (that website never really came to much, as we were pretty much on the way out when we set it up).

It was a bit of a culture shock, setting off from here where most of our neighbours are sheep and highland cattle in open fields, and arriving less than 24 later in central Tokyo where the sheeple are battery-farmed in a rather more intensive manner. However we are still probably more accustomed to life in Japan than the UK these days, so once we’d learnt the local train stations and lines (of which there are no fewer than four, most of which we hadn’t used much) it was plain sailing, and actually quite relaxing to be able to play the part of a short-term visitor rather than struggling to fit in as residents. We very much enjoyed the visit and hope to go back for more but didn’t think for a minute that we had made the wrong decision in leaving.

Thursday, February 12, 2015

I dunno, spend a couple of weeks out of the country and a proper debate strikes up for a change. Marotzke and Forster published this paper basically arguing that the AR5 models don't generally either over- or underestimate temperature changes, based on various trends within the last century or so (up to now). My first thought on a superficial glance at the paper was that it wasn't really that useful an analysis, as we already know that the models provide a decent hindcast of 20th century temps, so it's hardly surprising that looking at shorter trends will show the models agreeing on average over shorter trends too (since the full time series is merely the sum of shorter pieces). That leaves unasked the important question of how much the models have been tuned to reproduce the 20th century trend, and whether the recent divergence is the early signs of a problem or not. (Note that on the question of tuning, this is not even something that all modellers would have to be aware of, so honestly saying "we didn't do that" does not answer the question. But I digress.)

One limitation of the MF study was that they do not know the forcing for each model, or the α and κ parameters, so had to estimate them by linear regression based on (among other things) their temperature time series. Along comes Nic Lewis, and says "aha - this is circular". Now I haven't had time to look into it in detail, but this argument clearly has some validity in principle. MF replied here, but I'm not really impressed by what they said. There is a certain amount of talking past each other - MF are saying that their method is physically reasonable (which it is) and, in previous work, gives good results, however they don't really address the main criticism. Lewis says their method is simply invalid, because the assumptions underlying the statistical theory are violated. In that respect, it is worth pointing out that probably just about all statistical analysis is simply invalid at some level, since the assumptions are rarely precisely correct. Exact linearity, independent errors, gaussian statistics? You've got to be joking. These are never more than approximations to the truth, but hopefully the approximations are good enough that the end result is useful.

Some of the commenters on the climate lab book thread seem to have got a good handle on it. Just to expand on it a bit, if MF got the "correct" values for forcing, α and κ then it wouldn't matter where these numbers came from. However, there will be some uncertainty/inaccuracy in the estimates they have derived, and these did come from the temperature time series, and will lead to some circularity. So the question is really whether these inacuracies are big enough to matter. I have an idea for investigating the magnitude of the problem (which a priori could either be negligible or could indeed invalidate the work). I'm not sure it's really worth the effort though.

I was amused to see the different publicity, and reaction, to two pieces of research recently. The first was that silly article about running, which claimed that too much running is bad for you. Interestingly, that BBC page seems to have changed from the tautologous "too much" to the term "running hard", which if anything makes it worse, becaue too much being bad is just a definition of what too much means, whereas running hard...well that's where the research falls down. It only took a couple of mins to find the relevant paper, which shows...huge error bars on estimated risk for hard runners, such that the confidence interval on the hazard ratio actually goes below 1 (at which point running hard is good for you!). The underlying problem is that study was small, there were only 36(?) runners in this group, and this simply isn't enough to show conclusively what the health effects would be. I believe that More or Less has dealt with this, though I haven't listened to it yet.

Then just yesterday, David Spiegelhalter drew my attention to a study on the effects of alcohol, which claimed that modest drinking had no benefits (in opposition to the widely held view that it did). He explains that the study was again underpowered, such that any modest effect would by construction not be "statistically significant". The underlying problem is that, as Andrew Gelman often mentions, where an effect is probably small (but non-zero) and only weak studies with small samples are used, any "significant" result will necessarily be a huge overestimate of the effect (ie, if the true value is x but the error bar is ±10x then only estimates that come out to as much larger than x, and perhaps even with the wrong sign, can be reported as significant), and any realistic estimate close to the true value of x will be found "insignificant" and therefore be liable to being discarded or denied by silly scientists.

One obvious solution is to use a Bayesian approach with a reasonable prior, which in both cases would have found that the new data were insufficient to overturn what was previously believed to be the case...but that won't publish high profile papers or sell newspapers.

Wednesday, February 04, 2015

Sunday, February 01, 2015

So it is reported, anyway. No sign of anything official on the CD site, but the post by Crok seems to confirm it according to google translate. It is hardly a surprise, it was hardly a roaring success from the outset and the "dialogue" that I participated in was a turgid affair where the participants were repeatedly urged to add more comments long after it had become abundantly clear to all that no-one else was reading.

Crok is touting for alternatives/replacements, and I'm amused to see he explicitly calls out a couple of those who supposedly provide a link between the denialosphere and science. Certainly, there is a gap in the market for anyone who thinks it's a worthwhile exercise...

Saturday, January 31, 2015

It might appear a strangely familiar scene to my regular blog reader. Yes, jules and I are back in Japan, but it's only a visit this time, to our friend and colleagues in Tokyo University and NIES. Somehow we haven't found time to fit in a visit to JAMSTEC, but to be fair, it's the others who we actually collaborate with, and they are paying for the trip. Plenty of opportunity for blue skies research here in the winter!

With a weekend free (jules away on another engagement), I was keen to revisit some local hills, and also test out my new shoes (cheap midweight walking/running things). Some unusually heavy snowfall on Friday, in conjunction with my rather limited kit, almost put me off, but I shouldn't have been worried as 900m hills in Japan are pretty tame. Also, the snow being so fresh had not even had time to thaw and refreeze, so it was quite thick at the top but not very slippery. Ran up in a little over an hour, which gave me plenty of time to enjoy the rest of the day including a soak in the onsen at the bottom